Tanzu GemFire Memory Control: When to Expire Data, When to Evict It

Tanzu GemFire is an in-memory data grid designed for mission-critical workloads. It underpins real-time payments, credit card processing, transaction clearing, e-commerce, airline and transit ticketing, and defense systems. In these environments, data must be instantly available, trustworthy, and able to handle extreme concurrency.

As GemFire stores data in memory, and memory is finite, capacity management is essential. Horizontal scaling lets you add servers (and thus more memory capacity) and distribute data to more machines, but that alone isn’t enough. Policies that determine which data stays and which leaves are equally important. GemFire provides two mechanisms for this: Eviction and Expiration.

At first glance, both look similar since they remove data. The difference lies in intent: eviction protects the system under memory pressure, while expiration enforces data lifecycle rules.

Eviction: Guarding Against Memory Pressure

In GemFire, eviction is the safeguard that keeps regions from consuming more memory than they should. When a region reaches its configured threshold, GemFire reclaims space by removing older entries.

You can configure eviction to fit your workload. Eviction policies can be based on the number of entries, total memory used, or the percentage of JVM heap consumed. Once a limit is crossed, GemFire selects the least recently used entries and either destroys them or overflows them to disk.

Administrators define the eviction type, action, and thresholds that govern these decisions. This ensures each region stays within a fixed memory budget tied to the physical resources available. Eviction doesn’t care whether data is valid or current, it only enforces memory boundaries.

Common examples include capping a region at 8 GB of RAM, limiting it to 10 million entries, or constraining it to a percentage of the JVM heap.

Expiration: Enforcing Data Lifecycles

Expiration in GemFire ensures that your data remains fresh and relevant by automatically removing entries that have reached a time-based limit. Unlike eviction, which manages memory pressure, expiration focuses on enforcing data lifecycle rules regardless of available memory. This makes it ideal for time-sensitive information, keeping your cache lean, and ensuring your application always works with up-to-date data.

You can set expiration policies at either the entry level or the region level, giving you control over whether rules apply to individual records or to the entire dataset. The two standard types of expiration are time to live (TTL), which defines how long an entry or region can exist after creation or last update, and idle timeout, which defines how long data can remain unused before it expires.

At the entry level, for example, session tokens might expire 30 minutes after creation, or flight schedule entries could be removed if they haven’t been accessed for an hour.

At the region level, the entire dataset is governed by one clock. For instance, a DailyPricing region could be set with a 24-hour TTL so that all pricing data is automatically invalidated at midnight and replaced with a fresh daily load.

When data reaches its expiration threshold, GemFire applies the configured action. Entries can be destroyed, removing both key and value, or invalidated, clearing only the value but keeping the key. 

Conclusion: When to Expire Data, When to Evict It

Eviction and expiration serve very different purposes in GemFire. Eviction is about managing resources: it ensures regions stay within memory budgets, preventing your cluster from running into capacity issues. Expiration, on the other hand, is about managing data relevance: it ensures entries don’t outlive their usefulness, enforcing business rules and keeping your datasets fresh.

In real-world deployments, these mechanisms are often used together. Eviction acts as a safeguard against memory pressure, while expiration prevents applications from accessing stale data. Configuring both correctly gives you a predictable, reliable, and high-performing cluster. Think of eviction as a resource management tool and expiration as a lifecycle control, each addressing different aspects of data integrity and system stability.

By understanding and applying both, you can ensure your GemFire cluster not only runs efficiently but also aligns with your business requirements, maintaining fresh, accurate data while respecting the physical limits of your environment.